You have acknowledge fraud and high risks are a challenge for your organization. Furthermore, you have by now defined the issue and uncovered your organization’s weak spots, of which fraudsters will seamlessly take advantage. Also, you acknowledged that you (and fraudsters) are working in a digital insurance working space, which requires fraud fighting technology accordingly. Now what?
Aligning your organization and the key stakeholders of the various departments that need be involved can be a cumbersome process. At the end of the day, internal alignment (and commitment!) is a crucial factor in making your anti-fraud project a success. Who should be involved in your quest for a solution for automated fraud detection and risk analysis? How can you create a constructive and supportive environment for success? The guidelines can be used as a step in the right direction to align your organization in the fight against fraud.
An anti-fraud project is of interest for the entire organization. The right stakeholders should be involved at the right time, with most suitable approach. The guidelines help you to lay the foundation for your project and provides you with an approach on how you can get the various stakeholders onboard in order to make it a success.
6 learnings when starting an anti-fraud project:
1. An automated solution for insurance fraud detection and risk mitigation affects the entire organization.
2. Start with a proper description of the needs and requirements in a business case that shows the advantages for each and every stakeholder
3. To achieve a fraud fighting culture, senior management needs to be highly involved and KPIs should be aligned accordingly.
4. It is highly important to start timely. The project might, and probably will, not have the same priority as it has for you.
5. Be aware that even if all stakeholders are aligned, negotiations and discussion with other departments could take longer than expected.
6. The organization and the way processes are defined need to change as well. That can only be realized with a progressive and constructive foundation for the project.
Automated fraud detection
An automated solution for insurance fraud detection and risk mitigation can have a major impact on the way of working for the entire organization. It will improve the way staff work on a daily basis: more fraud awareness and more efficiency by resolving former cumbersome and error-prone manual processes. Above all, the new situation will directly contribute to the financial position of the company and the perception in the market as a trustworthy insurer.
A solution for automated fraud detection and risk mitigation helps insurers to improve combined ratios, lower loss ratios, enables straight through processing (STP/fast track) and helps to become digital. This will result in healthy (profitable) portfolios and contributes to an honest insurance industry. A fraud fighting culture and fraud awareness are essential to these objectives.
The business case
As shown, laying this foundation starts with a proper description of the needs and requirements for an automated fraud detection solution. The best way to do so is describing this in a business case that shows the advantages for each and every stakeholder, from IT to underwriting, from sales to claims and special investigations, from legal & compliance to board level.
Senior management involvement
To achieve a fraud fighting culture, senior management needs to be highly involved and set the example. The management should reward employees when suspicious behavior is detected and KPIs should be aligned accordingly, whilst taking into account the customer satisfaction or speed of handling policy applications or claims.
It is highly important to start timely. The project might, and probably will, not have the same priority as it has for you. Be aware that even if all stakeholders are aligned, negotiations and discussion with other departments could take longer than expected (e.g. legal). Another common challenge is the availability of data that is necessary to make proper indications of fraud or high risks. Therefore, have your IT department (and data scientists or analysts) sorted and prepared beforehand.